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A nonlinear model to estimate Nitrogen level in agricultural soil using Gaussian Kernels

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dc.contributor.author Sanchez-Mora, K es_PE
dc.contributor.author Zuniga-Gutierrez, MA es_PE
dc.contributor.author Mayhua-Lopez, E es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2016
dc.description.abstract Nitrogen fertilizers are commonly used to improve agricultural productivity. However, its excessive use may cause or lead to environmental problems. Therefore, technologies capable of monitoring and measure levels of nitrogen in agricultural soil in-situ and in real time are required in order to make efficient the use of fertilizers. Nitrogen levels are usually measured by direct and indirect methods. Direct methods can be conducted in-situ or in laboratory, but they are really expensive and/or little resistant to soil conditions.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1109/ANDESCON.2016.7836247
dc.identifier.isi 401925100060
dc.identifier.uri https://hdl.handle.net/20.500.12390/1011
dc.language.iso eng
dc.publisher IEEE
dc.rights info:eu-repo/semantics/openAccess
dc.subject fertilisers
dc.subject agriculture es_PE
dc.subject electrical conductivity es_PE
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#4.01.01
dc.title A nonlinear model to estimate Nitrogen level in agricultural soil using Gaussian Kernels
dc.type info:eu-repo/semantics/conferenceObject
dspace.entity.type Publication
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